The AI Front Lines

About The AI Front Lines

Conversations with founders building the future of AI.

Publisher

The Front Lines

Category

business

Language

en

Explicit

No

First episode

3 Aug 2022

Latest episode

20 Aug 2026

Latest episodes

93 episodes in the feed.

1. 

   20 Aug 2026

   The head of AI who had never heard of an ontology | Rob Buller

   Cyberhill Partners builds and deploys enterprise AI solutions, including Cerebro, an enterprise AI platform Rob describes as AI in a box, and Wolverine, a digital twin product, drawing on eight years of AI work inside the intelligence community. In a recent episode of BUILDERS, we sat down with ⁠Rob Buller⁠ (https://www.linkedin.com/in/rob-buller-97292/), Chief Executive Officer of ⁠Cyberhill Partners⁠ (https://cyberhillpartners.com/), to learn how the company is bringing intelligence-community-grade AI to enterprise buyers who are still missing the semantic layer that makes AI work. Topics Discussed: Why the core principles of technology adoption have not changed, but complexity has, splitting the buyer across CIOs, CTOs, and CISOs The AI factory model: a runtime AI fabric that plugs into Snowflake, Databricks, Grok, or Gemini instead of shipping compiled, embedded logic How Cyberhill positions Cerebro against Palantir on cost, vendor lock-in, and implementation speed Why Rob has been shocked that heads of AI at multi-billion dollar companies do not know what an ontology is How large incumbents like Workday and Salesforce try to freeze the market when new technology emerges Why Cyberhill picks verticals by following demand into government, automotive, and healthcare Marketing at the local level in secondary markets like Dallas and Denver with billboards, airports, and quarterly steak dinners Partnerships with ServiceNow and Databricks, and government AI work including a global biosurveillance platform GTM & Technology Adoption Lessons: The market cannot buy what it does not understand: Rob has been on roughly a hundred client calls where heads of AI at multi-billion dollar companies could not define an ontology. Without the semantic layer, he argues, you cannot apply context to AI or get traceability. Until buyers understand that, adoption stalls, so education is now part of the sales motion whether Cyberhill wants it or not. Sell the problem solved, not the underlying technology: "People don't care about ontologies and knowledge graphs, they care about can you solve my problem." Cyberhill leads with the business problem and only opens up the technical underpinnings when a buyer wants to know why the product is different. Expect incumbents to freeze the market: Rob says large companies respond to new AI entrants by telling customers they already have AI covered. He admits it does not really work, but it works a little bit. Plan the GTM knowing buyers are hearing "you don't need AI" from vendors they already pay. Let demand pick your verticals: "I've found that business is a lot like water. It finds the lowest level." Rather than forcing a vertical strategy, Cyberhill follows where demand shows up: government, automotive, healthcare. When healthcare demand grew, the company hired a doctor, because subject matter experts are how it enters an industry credibly. Position against the expensive incumbent on speed to value: Rob calls Palantir a great company and a great platform, but points to cost and vendor lock-in. Cyberhill's counter is malleability and implementation speed: "we can implement it in days, not months." Compete where the playing field is level: Instead of fighting Salesforce for attention in New York, LA, and San Francisco, Cyberhill markets at the local level in secondary markets like Dallas and Denver, with billboards, airport advertising, and quarterly steak dinners. Own the category conversation before the window closes: Rob predicts everybody will be talking about the semantic layer in enterprise AI within three years, if not sooner. He also acknowledges the loudest technology does oftentimes win, which makes owning that conversation early a strategic requirement, not a vanity project. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

2. 

   17 Aug 2026

   The 90% trust artifact that opened OPAQUE's market | Aaron Fulkerson

   In a recent episode of BUILDERS, we sat down with ⁠Aaron Fulkerson⁠ (https://www.linkedin.com/in/aaronfulkerson/), CEO of ⁠OPAQUE⁠ (https://www.opaque.co/), to learn how the company found its market in sovereign AI deployments after discovering that customers would accept 90% verifiability with known gaps rather than waiting for perfect end-to-end confidential computation. Topics Discussed: Why Aaron joined OPAQUE from ServiceNow only after the founders agreed to apply the technology to language models How generative AI systems leak data by architecture, and why that threatens both enterprises and frontier labs The first customer: a European Union cybersecurity agency running analytics and ML How the focus evolved from high tech to regulated industries to sovereign deployments over roughly sixteen months The 2025 realization that a trust artifact with 90% verifiability and known gaps was good enough for customers Turning down a nation-state-scale sovereign deployment in the UAE, and how that honesty turned the entity into a Series B investor Why OPAQUE handed the Confidential Computing Summit to the Linux Foundation What Apple's private cloud compute expansion signals for enterprise AI adoption GTM & Technology Adoption Lessons: Refuse to commercialize the wrong product: Before joining, Aaron told the founders that if the product did not involve language models, it was probably not interesting and would be too difficult to build a commercial effort around. The replatforming from confidential Spark analytics to language models started essentially on day one. Let customers define good enough: OPAQUE assumed it needed end-to-end confidential computation across CPUs and GPUs, but confidential GPU availability through hyperscalers was slow. The company discovered through customers that a trust artifact delivering roughly 90% verifiability of policies, with known gaps, was acceptable. Aaron called it a we-have-been-overthinking-this moment. Honesty about scale limits can win the deal: When a UAE entity wanted OPAQUE to roll out as part of a sovereign stack for a 13 gigawatt build-out, Aaron told them nation-state scale was not deliverable in 2025, since the company had just put its first customers into production. OPAQUE took on two or three enterprise-scale projects instead, and the entity became an investor in the Series B round. Follow the pain into regulated industries: The initial focus was high tech, but OPAQUE learned that regulated industries with strict requirements had the real urgency. Just over a year before the conversation, the company shifted focus to sovereign deployments: healthcare data, banking data, and high tech that is critical infrastructure. Build the ecosystem, not just the brand: OPAQUE hosts the Confidential Computing Summit, which grew until the Linux Foundation became co-host and took ownership. Aaron's view is that no one entity can own the digital sovereignty conversation; OPAQUE needs Google, Microsoft, and Apple building interoperability for the category to exist. Use the anchor example customers already trust: Aaron points to Apple architecting Siri's Gemini-powered processing to be confidential end-to-end. If a basic chatbot was too great a data leakage risk for Apple, enterprises running far leakier AI agents on far more valuable data have their answer. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

3. 

   17 Jul 2026

   How Guild AI discovered their real buyers weren't developers — and rebuilt their GTM motion around CIOs and CSOs | James Everingham

   Guild AI is building the infrastructure layer that enterprises need to deploy, manage, and govern AI agents operating inside their systems. Founded by ⁠James Everingham⁠ (https://www.linkedin.com/in/jevering/) — a five-time founder who most recently led developer infrastructure at Meta, overseeing a team of more than a thousand engineers — ⁠Guild AI⁠ (https://www.guild.ai/) is solving a problem James watched emerge firsthand inside one of the world's most complex technology organizations: what happens when agents stop being prototypes and start taking autonomous action inside your production infrastructure. In this episode of BUILDERS, James shares what he's learned about founding companies across nearly four decades, from writing shareware in central Pennsylvania in 1987 to building developer tooling at Meta to launching Guild AI. He goes deep on why the go-to-market motion for a new infrastructure category defaults tops-down, what enterprise engineering leaders actually respond to from vendors, and the product philosophy he's refined across five companies. Topics Discussed: Why James founded Guild AI after watching agent adoption break at scale inside Meta How Guild AI's go-to-market shifted from developer-led to CIO/CSO/CTO-driven — and what forced that shift Why design partners pushed Guild AI's use cases away from software development and into legal, marketing, HR, and finance What vendors consistently got wrong when trying to sell to James at Meta — and what actually worked GTM Lessons For B2B Founders: New infrastructure categories require a tops-down entry: Guild AI initially assumed a bottoms-up, developer-led motion. Their design partners revealed quickly that CIOs, CSOs, and CTOs were the ones carrying the urgency around agent governance — not individual developers. James frames the dynamic precisely: in early markets where buyers lack a clear starting point, individual contributors won't self-organize around a new tool without leadership buy-in first. The tops-down entry earns executive trust, establishes the governance framework, and creates the conditions for developers to adopt the tooling on their own terms — without a mandate. Follow your design partners, not your original thesis: Guild AI launched with a developer productivity thesis. Their earliest design partners pulled them toward marketing, legal, HR, and finance — areas where, as James noted, there's likely more demand for agentic workflow automation than in software development itself. The team followed the signal rather than defending the thesis. For B2B founders in emerging categories, design partnerships aren't just validation — they're navigation. The customers who show up first will often redirect you toward the higher-value problem you hadn't fully seen yet. Enterprise outreach is pattern-matched and rejected in seconds: James was receiving vendor pitches at Meta at scale. What killed deals before they started: AI-generated emails that reflected his own company's marketing language back at him with light personalization layered on top. His analogy is precise — he compares it to the first banner ads on the internet, effective for about three months before everyone learned to ignore them. // Sponsors: Front Lines — We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership.⁠ www.FrontLines.io⁠ (http://www.frontlines.io) The Global Talent Co. — We help tech startups find, vet, hire, pay, and retain amazing marketing talent that costs 50-70% less than the US & Europe.⁠ www.GlobalTalent.co⁠ (http://www.globaltalent.co) // Don't Miss: New Podcast Series — How I Hire Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role. Subscribe here:⁠ https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM⁠ (https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM)

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